CE_LDR (Implementation of "Contrast Enhancement Based on Layered Difference Representation of 2D Histograms")

This Python script implements the image contrast enhancement algorithm described in the paper "Contrast Enhancement Based on Layered Difference Representation of 2D Histograms."

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Algorithm

The core logic of this script is based on the method detailed in the scientific publication: "Contrast Enhancement Based on Layered Difference Representation of 2D Histograms." For a comprehensive understanding of the underlying principles, mathematical formulations, and evaluation, please refer to the original paper.

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Dependencies

To run CE_LDR.py, you need the following Python libraries:

• NumPy: For numerical operations, especially array manipulations.
• Pillow (PIL): For image file loading and handling.
• Matplotlib: For displaying images.

You can install these dependencies using pip:

pip install numpy Pillow matplotlib

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Usage

a. Navigate to the project directory:

cd /path/to/CE_LDR/

(Replace /path/to/CE_LDR/ with the actual path to the directory containing CE_LDR.py)

b. Execute the script:

The script is run from the command line with the following syntax:

python CE_LDR.py --input_path ${INPUT_PATH} [--alpha ${ALPHA}] [--U ${U_PATH}]

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Parameters

• --input_path ${INPUT_PATH} (required):

  • Specifies the path to the input image file that you want to enhance.
  • Example: images/my_photo.jpg, ../data/landscape.png.

• --alpha ${ALPHA} (optional):

  • A floating-point number that controls the intensity of the contrast enhancement.
  • Higher values generally lead to stronger enhancement.
  • If not specified, this parameter defaults to 2.5.
  • Example: --alpha 3.0.

• --U ${U_PATH} (optional):

  • Specifies the path to a .npy file that contains the U matrix used in equation 31 of the paper. This matrix is part of the Layered Difference Representation.
  • The matrix stored in the .npy file should have a shape of (255, 255).
  • If this parameter is not provided, the script will calculate a default U matrix based on the algorithm's formulas.
  • Example: --U my_custom_U_matrix.npy.

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Output

When CE_LDR.py is executed:

1. Image Display:

   • The original input image will be displayed in a Matplotlib window.
   • After processing, the contrast-enhanced image will be displayed in a new Matplotlib window.

2. Saved Image:

   • The enhanced image is saved as a PNG file in the same directory where the CE_LDR.py script is located.
   • The output filename is generated based on the input filename using the format: ce_<original_filename_without_extension>_<original_extension>.png.
   • For example:
     • If input is test.png, output will be ce_test_png.png.
     • If input is ../images/sample.jpg, output will be ce_sample_jpg.png.

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